We compared our proposed method with two conventional t-MRI motion tracking methods. The first one is HARP [1]}. We reimplemented it in MATLAB (R2019a). Another one is the variational OF methodCode is online http://www.iv.optica.csic.es/page49/page54/page54.html [2]}, which uses a total variation (TV) regularization term.
We also compared our method with the unsupervised deep learning-based medical image registration methods VM [3]} and VM-DIF [4]}, which are recent cutting-edge unsupervised image registration approaches. VM uses SSD (MSE) or NCC loss for training, while VM-DIF uses SSD loss. We used their official implementation code onlinehttps://github.com/voxelmorph/voxelmorph, and trained VM and VM-DIF from scratch by following the optimal hyper-parameters suggested by the authors.
